import os
from glob import glob
import csv
import cv2
import numpy as np
import matplotlib.pyplot as plt
import random

TRUE_IMG_PATH='./True/'
FALSE_IMG_PATH='./False/'
pixel_size=224


true_imgs=glob(TRUE_IMG_PATH+'*')
false_imgs=glob(FALSE_IMG_PATH+'*')
all_imgs=true_imgs+false_imgs

print(len(true_imgs))
print (len(false_imgs))

len_imgs=len(true_imgs)+len(false_imgs)

x_input=np.array((len_imgs,pixel_size,pixel_size,1))
x_label=[]

true_label=[]
false_label=[]

def read_img_label(img_list,label):
    label_list=[]
    imgs_array=np.zeros((len(img_list),pixel_size,pixel_size,1))
    for i,img in enumerate(img_list):
        img_array=cv2.resize(cv2.imread(img,0),(pixel_size,pixel_size))
        label_list.append(label)
        imgs_array[i,:,:,0]=img_array
    label_list=np.array(label_list)
    return imgs_array,label_list
        
true_inputs,true_labels = read_img_label(true_imgs,[0,1])
false_inputs,false_labels = read_img_label(false_imgs,[1,0])

113
46

print (true_inputs.shape)

plt.imshow(true_inputs[10,:,:,0],cmap=plt.cm.gray)
plt.show()

def shuffle_data(a,b,r1):
    assert len(a)==len(b)
    r=list(range(len(a)))
    random.shuffle(r,lambda: r1)
    p=np.array(r)
    
    return a[p],b[p]


data=np.vstack((true_inputs,false_inputs))
labels=np.vstack((true_labels,false_labels))


data,labels=shuffle_data(data,labels,0.1)


split_point=int(round(0.8*len(data)))
(x_train,x_val)=(data[:split_point],data[split_point:])
(y_train,y_val)= (labels[:split_point],labels[split_point:])

# (x_train, y_train), (x_val, y_val) = mnist.load_data()

(113, 224, 224, 1)

from keras.applications import ResNet50
from vis.utils import utils
from keras import activations
from keras.layers import Dense, GlobalAveragePooling2D,BatchNormalization,Activation, Flatten,AveragePooling2D, Input
from keras.models import Model


# Hide warnings on Jupyter Notebook
import warnings
warnings.filterwarnings('ignore')

# Build the ResNet50 network with ImageNet weights
input_shape=(224,224, 1)
model = ResNet50(weights=None, include_top=False, input_shape=input_shape,classes =2)

# model.summary()

# input = Input(shape=input_shape)
input = model.input

x = model.output
x = Activation('relu')(x)
x = BatchNormalization()(x)

x = AveragePooling2D()(x)

print (x.shape)

x = Flatten()(x)

dense = Dense(2,activation='softmax')(x)


model = Model(inputs=input, outputs=dense)

Using TensorFlow backend.

(?, 3, 3, 2048)

import numpy as np
import keras

from keras.datasets import mnist
from keras.models import Sequential, Model
from keras.layers import Dense, Dropout, Flatten, Activation, Input
from keras.layers import Conv2D, MaxPooling2D
from keras import backend as K
from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten
from keras.layers import Conv2D, MaxPooling2D
import os
from keras.layers.normalization import BatchNormalization
from keras.callbacks import ReduceLROnPlateau, CSVLogger, EarlyStopping

from keras.datasets import cifar10
from keras.preprocessing.image import ImageDataGenerator
from keras.utils import np_utils
from keras.callbacks import ReduceLROnPlateau, CSVLogger, EarlyStopping

import numpy as np
import resnet

os.environ["CUDA_VISIBLE_DEVICES"] = '0'


lr_reducer = ReduceLROnPlateau(factor=np.sqrt(0.1), cooldown=0, patience=5, min_lr=0.5e-6)
early_stopper = EarlyStopping(min_delta=0.001, patience=10)
# csv_logger = CSVLogger('resnet18_cifar10.csv')

batch_size = 32
nb_classes = 2
nb_epoch = 250
data_augmentation = True

# input image dimensions
img_rows, img_cols = 224, 224
# The CIFAR10 images are RGB.
img_channels = 1




model.compile(loss='categorical_crossentropy',
              optimizer='adam',
              metrics=['accuracy'])



if not data_augmentation:
    print('Not using data augmentation.')
    model.fit(x_train, y_train,
              batch_size=batch_size,
              nb_epoch=nb_epoch,
              validation_data=(x_val, y_val),
              shuffle=True,
              callbacks=[lr_reducer, early_stopper])
else:
    print('Using real-time data augmentation.')
    # This will do preprocessing and realtime data augmentation:
    datagen = ImageDataGenerator(
        featurewise_center=False,  # set input mean to 0 over the dataset
        samplewise_center=False,  # set each sample mean to 0
        featurewise_std_normalization=False,  # divide inputs by std of the dataset
        samplewise_std_normalization=False,  # divide each input by its std
        zca_whitening=False,  # apply ZCA whitening
        rotation_range=0,  # randomly rotate images in the range (degrees, 0 to 180)
        width_shift_range=0.1,  # randomly shift images horizontally (fraction of total width)
        height_shift_range=0.1,  # randomly shift images vertically (fraction of total height)
        horizontal_flip=True,  # randomly flip images
        vertical_flip=False)  # randomly flip images

    # Compute quantities required for featurewise normalization
    # (std, mean, and principal components if ZCA whitening is applied).
    datagen.fit(x_train)

    # Fit the model on the batches generated by datagen.flow().
    model.fit_generator(datagen.flow(x_train, y_train, batch_size=batch_size),
                        steps_per_epoch=x_train.shape[0] // batch_size,
                        validation_data=(x_val, y_val),
                        epochs=nb_epoch, verbose=1, max_q_size=100,
                        callbacks=[lr_reducer])

Using real-time data augmentation.
Epoch 1/250
3/3 [==============================] - 12s 4s/step - loss: 1.6029 - acc: 0.6625 - val_loss: 13.2023 - val_acc: 0.1250
Epoch 2/250
3/3 [==============================] - 1s 243ms/step - loss: 1.2281 - acc: 0.8421 - val_loss: 13.6004 - val_acc: 0.1562
Epoch 3/250
3/3 [==============================] - 1s 187ms/step - loss: 1.1374 - acc: 0.8333 - val_loss: 13.5685 - val_acc: 0.1250
Epoch 4/250
3/3 [==============================] - 1s 188ms/step - loss: 1.0393 - acc: 0.8739 - val_loss: 13.3425 - val_acc: 0.1562
Epoch 5/250
3/3 [==============================] - 1s 186ms/step - loss: 0.6721 - acc: 0.8739 - val_loss: 13.9465 - val_acc: 0.1250
Epoch 6/250
3/3 [==============================] - 1s 188ms/step - loss: 0.4732 - acc: 0.8951 - val_loss: 13.9365 - val_acc: 0.1250
Epoch 7/250
3/3 [==============================] - 1s 187ms/step - loss: 0.6108 - acc: 0.9271 - val_loss: 13.3865 - val_acc: 0.1250
Epoch 8/250
3/3 [==============================] - 1s 188ms/step - loss: 0.5390 - acc: 0.9264 - val_loss: 13.1630 - val_acc: 0.1250
Epoch 9/250
3/3 [==============================] - 1s 185ms/step - loss: 0.3506 - acc: 0.9582 - val_loss: 11.5725 - val_acc: 0.1250
Epoch 10/250
3/3 [==============================] - 1s 187ms/step - loss: 0.1625 - acc: 0.9261 - val_loss: 10.2172 - val_acc: 0.1875
Epoch 11/250
3/3 [==============================] - 1s 190ms/step - loss: 0.4151 - acc: 0.9062 - val_loss: 7.4806 - val_acc: 0.2812
Epoch 12/250
3/3 [==============================] - 1s 187ms/step - loss: 0.3085 - acc: 0.9259 - val_loss: 5.8677 - val_acc: 0.4062
Epoch 13/250
3/3 [==============================] - 1s 187ms/step - loss: 0.3048 - acc: 0.9371 - val_loss: 5.4077 - val_acc: 0.5000
Epoch 14/250
3/3 [==============================] - 1s 188ms/step - loss: 0.2418 - acc: 0.9580 - val_loss: 5.4006 - val_acc: 0.5312
Epoch 15/250
3/3 [==============================] - 1s 190ms/step - loss: 0.1118 - acc: 0.9375 - val_loss: 4.2844 - val_acc: 0.5312
Epoch 16/250
3/3 [==============================] - 1s 187ms/step - loss: 0.4546 - acc: 0.8846 - val_loss: 3.4438 - val_acc: 0.5000
Epoch 17/250
3/3 [==============================] - 1s 188ms/step - loss: 0.3625 - acc: 0.8958 - val_loss: 3.0097 - val_acc: 0.5938
Epoch 18/250
3/3 [==============================] - 1s 185ms/step - loss: 0.3012 - acc: 0.9254 - val_loss: 3.3761 - val_acc: 0.5000
Epoch 19/250
3/3 [==============================] - 1s 189ms/step - loss: 0.2005 - acc: 0.9167 - val_loss: 3.2513 - val_acc: 0.5312
Epoch 20/250
3/3 [==============================] - 1s 188ms/step - loss: 0.2299 - acc: 0.9577 - val_loss: 2.9511 - val_acc: 0.6875
Epoch 21/250
3/3 [==============================] - 1s 185ms/step - loss: 0.2138 - acc: 0.9791 - val_loss: 2.9727 - val_acc: 0.6875
Epoch 22/250
3/3 [==============================] - 1s 188ms/step - loss: 0.1045 - acc: 0.9470 - val_loss: 2.8080 - val_acc: 0.6875
Epoch 23/250
3/3 [==============================] - 1s 189ms/step - loss: 0.2454 - acc: 0.9479 - val_loss: 2.6158 - val_acc: 0.6875
Epoch 24/250
3/3 [==============================] - 1s 187ms/step - loss: 0.2521 - acc: 0.9684 - val_loss: 2.4332 - val_acc: 0.6875
Epoch 25/250
3/3 [==============================] - 1s 188ms/step - loss: 0.2944 - acc: 0.9366 - val_loss: 2.2106 - val_acc: 0.6875
Epoch 26/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0843 - acc: 0.9682 - val_loss: 2.3073 - val_acc: 0.6875
Epoch 27/250
3/3 [==============================] - 1s 189ms/step - loss: 0.2389 - acc: 0.9475 - val_loss: 2.3587 - val_acc: 0.7187
Epoch 28/250
3/3 [==============================] - 1s 189ms/step - loss: 0.2898 - acc: 0.9479 - val_loss: 2.2320 - val_acc: 0.7500
Epoch 29/250
3/3 [==============================] - 1s 187ms/step - loss: 0.3702 - acc: 0.9684 - val_loss: 2.2138 - val_acc: 0.7500
Epoch 30/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0673 - acc: 0.9684 - val_loss: 2.0722 - val_acc: 0.7500
Epoch 31/250
3/3 [==============================] - 1s 190ms/step - loss: 0.2514 - acc: 0.9688 - val_loss: 1.6406 - val_acc: 0.7500
Epoch 32/250
3/3 [==============================] - 1s 186ms/step - loss: 0.3011 - acc: 0.9473 - val_loss: 1.4230 - val_acc: 0.7812
Epoch 33/250
3/3 [==============================] - 1s 185ms/step - loss: 0.0584 - acc: 0.9789 - val_loss: 1.5884 - val_acc: 0.8125
Epoch 34/250
3/3 [==============================] - 1s 187ms/step - loss: 0.1761 - acc: 0.9375 - val_loss: 1.8783 - val_acc: 0.7500
Epoch 35/250
3/3 [==============================] - 1s 187ms/step - loss: 0.1082 - acc: 0.9266 - val_loss: 2.0066 - val_acc: 0.6250
Epoch 36/250
3/3 [==============================] - 1s 187ms/step - loss: 0.1183 - acc: 0.9475 - val_loss: 2.0361 - val_acc: 0.7188
Epoch 37/250
3/3 [==============================] - 1s 188ms/step - loss: 0.2067 - acc: 0.9366 - val_loss: 1.6249 - val_acc: 0.7500
Epoch 38/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0807 - acc: 0.9583 - val_loss: 1.5640 - val_acc: 0.7500
Epoch 39/250
3/3 [==============================] - 1s 187ms/step - loss: 0.1193 - acc: 0.9686 - val_loss: 1.4577 - val_acc: 0.7812
Epoch 40/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0647 - acc: 0.9792 - val_loss: 1.4237 - val_acc: 0.7812
Epoch 41/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0532 - acc: 0.9896 - val_loss: 1.4284 - val_acc: 0.7812
Epoch 42/250
3/3 [==============================] - 1s 185ms/step - loss: 0.0382 - acc: 0.9896 - val_loss: 1.4127 - val_acc: 0.7812
Epoch 43/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0115 - acc: 1.0000 - val_loss: 1.3802 - val_acc: 0.8125
Epoch 44/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0120 - acc: 1.0000 - val_loss: 1.3483 - val_acc: 0.8125
Epoch 45/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0556 - acc: 0.9896 - val_loss: 1.1895 - val_acc: 0.8125
Epoch 46/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0226 - acc: 0.9896 - val_loss: 0.9899 - val_acc: 0.8438
Epoch 47/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0185 - acc: 1.0000 - val_loss: 0.8778 - val_acc: 0.8438
Epoch 48/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0356 - acc: 0.9893 - val_loss: 0.8108 - val_acc: 0.8438
Epoch 49/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0880 - acc: 0.9791 - val_loss: 0.8012 - val_acc: 0.8438
Epoch 50/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0718 - acc: 0.9792 - val_loss: 0.8413 - val_acc: 0.8125
Epoch 51/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0150 - acc: 1.0000 - val_loss: 0.9073 - val_acc: 0.8125
Epoch 52/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0177 - acc: 0.9896 - val_loss: 0.9688 - val_acc: 0.8125
Epoch 53/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0405 - acc: 0.9893 - val_loss: 0.9769 - val_acc: 0.8125
Epoch 54/250
3/3 [==============================] - 1s 185ms/step - loss: 0.0411 - acc: 0.9789 - val_loss: 0.9595 - val_acc: 0.8125
Epoch 55/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0906 - acc: 0.9792 - val_loss: 0.9523 - val_acc: 0.8125
Epoch 56/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0219 - acc: 1.0000 - val_loss: 0.9446 - val_acc: 0.8125
Epoch 57/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0289 - acc: 0.9791 - val_loss: 0.9447 - val_acc: 0.8125
Epoch 58/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0124 - acc: 1.0000 - val_loss: 0.9429 - val_acc: 0.8125
Epoch 59/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0082 - acc: 1.0000 - val_loss: 0.9484 - val_acc: 0.8125
Epoch 60/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0063 - acc: 1.0000 - val_loss: 0.9513 - val_acc: 0.8125
Epoch 61/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0412 - acc: 0.9789 - val_loss: 0.9558 - val_acc: 0.8125
Epoch 62/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0149 - acc: 0.9896 - val_loss: 0.9565 - val_acc: 0.8125
Epoch 63/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0167 - acc: 0.9896 - val_loss: 0.9532 - val_acc: 0.8125
Epoch 64/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0096 - acc: 1.0000 - val_loss: 0.9451 - val_acc: 0.8125
Epoch 65/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0140 - acc: 1.0000 - val_loss: 0.9441 - val_acc: 0.8125
Epoch 66/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0533 - acc: 0.9896 - val_loss: 0.9434 - val_acc: 0.8125
Epoch 67/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0978 - acc: 0.9786 - val_loss: 0.9429 - val_acc: 0.8125
Epoch 68/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0169 - acc: 1.0000 - val_loss: 0.9421 - val_acc: 0.8125
Epoch 69/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0357 - acc: 0.9789 - val_loss: 0.9384 - val_acc: 0.8125
Epoch 70/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0193 - acc: 1.0000 - val_loss: 0.9391 - val_acc: 0.8125
Epoch 71/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0163 - acc: 0.9896 - val_loss: 0.9397 - val_acc: 0.8125
Epoch 72/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0193 - acc: 1.0000 - val_loss: 0.9383 - val_acc: 0.8125
Epoch 73/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0280 - acc: 0.9789 - val_loss: 0.9377 - val_acc: 0.8125
Epoch 74/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0169 - acc: 0.9896 - val_loss: 0.9412 - val_acc: 0.8125
Epoch 75/250
3/3 [==============================] - 1s 191ms/step - loss: 0.0389 - acc: 0.9896 - val_loss: 0.9444 - val_acc: 0.8125
Epoch 76/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0197 - acc: 0.9896 - val_loss: 0.9446 - val_acc: 0.8125
Epoch 77/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0547 - acc: 0.9684 - val_loss: 0.9445 - val_acc: 0.8125
Epoch 78/250
3/3 [==============================] - 1s 191ms/step - loss: 0.0037 - acc: 1.0000 - val_loss: 0.9453 - val_acc: 0.8125
Epoch 79/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0299 - acc: 0.9896 - val_loss: 0.9497 - val_acc: 0.8125
Epoch 80/250
3/3 [==============================] - 1s 191ms/step - loss: 0.1711 - acc: 0.9368 - val_loss: 0.9532 - val_acc: 0.8125
Epoch 81/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0114 - acc: 1.0000 - val_loss: 0.9509 - val_acc: 0.8125
Epoch 82/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0613 - acc: 0.9893 - val_loss: 0.9542 - val_acc: 0.8125
Epoch 83/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0451 - acc: 0.9896 - val_loss: 0.9587 - val_acc: 0.8125
Epoch 84/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0382 - acc: 0.9791 - val_loss: 0.9611 - val_acc: 0.8125
Epoch 85/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0054 - acc: 1.0000 - val_loss: 0.9624 - val_acc: 0.8125
Epoch 86/250
3/3 [==============================] - 1s 191ms/step - loss: 0.0144 - acc: 1.0000 - val_loss: 0.9638 - val_acc: 0.8125
Epoch 87/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0194 - acc: 1.0000 - val_loss: 0.9641 - val_acc: 0.8125
Epoch 88/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0142 - acc: 1.0000 - val_loss: 0.9686 - val_acc: 0.8125
Epoch 89/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0123 - acc: 1.0000 - val_loss: 0.9685 - val_acc: 0.8125
Epoch 90/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0428 - acc: 0.9896 - val_loss: 0.9734 - val_acc: 0.8125
Epoch 91/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0173 - acc: 1.0000 - val_loss: 0.9758 - val_acc: 0.8125
Epoch 92/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0136 - acc: 1.0000 - val_loss: 0.9760 - val_acc: 0.8125
Epoch 93/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0176 - acc: 1.0000 - val_loss: 0.9761 - val_acc: 0.8125
Epoch 94/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0143 - acc: 1.0000 - val_loss: 0.9780 - val_acc: 0.8125
Epoch 95/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0154 - acc: 1.0000 - val_loss: 0.9820 - val_acc: 0.8125
Epoch 96/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0094 - acc: 1.0000 - val_loss: 0.9839 - val_acc: 0.8125
Epoch 97/250
3/3 [==============================] - 1s 188ms/step - loss: 0.1611 - acc: 0.9679 - val_loss: 0.9879 - val_acc: 0.8125
Epoch 98/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0090 - acc: 1.0000 - val_loss: 0.9877 - val_acc: 0.8125
Epoch 99/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0177 - acc: 1.0000 - val_loss: 0.9866 - val_acc: 0.8125
Epoch 100/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0142 - acc: 0.9896 - val_loss: 0.9898 - val_acc: 0.8125
Epoch 101/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0210 - acc: 1.0000 - val_loss: 0.9932 - val_acc: 0.8125
Epoch 102/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0258 - acc: 0.9792 - val_loss: 0.9950 - val_acc: 0.8125
Epoch 103/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0590 - acc: 0.9684 - val_loss: 0.9943 - val_acc: 0.8125
Epoch 104/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0314 - acc: 0.9896 - val_loss: 0.9972 - val_acc: 0.8125
Epoch 105/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0275 - acc: 0.9789 - val_loss: 0.9993 - val_acc: 0.7812
Epoch 106/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0115 - acc: 1.0000 - val_loss: 1.0025 - val_acc: 0.7812
Epoch 107/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0127 - acc: 1.0000 - val_loss: 1.0032 - val_acc: 0.7812
Epoch 108/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0043 - acc: 1.0000 - val_loss: 1.0016 - val_acc: 0.7812
Epoch 109/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0181 - acc: 1.0000 - val_loss: 1.0044 - val_acc: 0.7812
Epoch 110/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0456 - acc: 0.9682 - val_loss: 1.0042 - val_acc: 0.7812
Epoch 111/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0145 - acc: 1.0000 - val_loss: 1.0038 - val_acc: 0.7812
Epoch 112/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0226 - acc: 1.0000 - val_loss: 1.0054 - val_acc: 0.7812
Epoch 113/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0134 - acc: 1.0000 - val_loss: 1.0076 - val_acc: 0.7812
Epoch 114/250
3/3 [==============================] - 1s 185ms/step - loss: 0.0116 - acc: 1.0000 - val_loss: 1.0051 - val_acc: 0.7812
Epoch 115/250
3/3 [==============================] - 1s 191ms/step - loss: 0.0250 - acc: 0.9896 - val_loss: 1.0070 - val_acc: 0.7812
Epoch 116/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0154 - acc: 0.9896 - val_loss: 1.0078 - val_acc: 0.7812
Epoch 117/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0189 - acc: 1.0000 - val_loss: 1.0099 - val_acc: 0.7812
Epoch 118/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0275 - acc: 1.0000 - val_loss: 1.0117 - val_acc: 0.7812
Epoch 119/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0117 - acc: 0.9896 - val_loss: 1.0099 - val_acc: 0.7812
Epoch 120/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0160 - acc: 1.0000 - val_loss: 1.0117 - val_acc: 0.7812
Epoch 121/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0169 - acc: 1.0000 - val_loss: 1.0136 - val_acc: 0.7812
Epoch 122/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0623 - acc: 0.9788 - val_loss: 1.0168 - val_acc: 0.7812
Epoch 123/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0538 - acc: 0.9896 - val_loss: 1.0135 - val_acc: 0.7812
Epoch 124/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0086 - acc: 1.0000 - val_loss: 1.0153 - val_acc: 0.7812
Epoch 125/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0116 - acc: 1.0000 - val_loss: 1.0163 - val_acc: 0.7812
Epoch 126/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0458 - acc: 0.9791 - val_loss: 1.0151 - val_acc: 0.7812
Epoch 127/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0483 - acc: 0.9893 - val_loss: 1.0146 - val_acc: 0.7812
Epoch 128/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0137 - acc: 1.0000 - val_loss: 1.0187 - val_acc: 0.7812
Epoch 129/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0146 - acc: 0.9896 - val_loss: 1.0203 - val_acc: 0.7812
Epoch 130/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0322 - acc: 0.9893 - val_loss: 1.0219 - val_acc: 0.7812
Epoch 131/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0049 - acc: 1.0000 - val_loss: 1.0268 - val_acc: 0.7812
Epoch 132/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0081 - acc: 1.0000 - val_loss: 1.0260 - val_acc: 0.7812
Epoch 133/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0254 - acc: 1.0000 - val_loss: 1.0281 - val_acc: 0.7812
Epoch 134/250
3/3 [==============================] - 1s 191ms/step - loss: 0.0049 - acc: 1.0000 - val_loss: 1.0299 - val_acc: 0.7812
Epoch 135/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0225 - acc: 1.0000 - val_loss: 1.0304 - val_acc: 0.7812
Epoch 136/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0093 - acc: 1.0000 - val_loss: 1.0316 - val_acc: 0.7812
Epoch 137/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0645 - acc: 0.9580 - val_loss: 1.0342 - val_acc: 0.7812
Epoch 138/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0224 - acc: 1.0000 - val_loss: 1.0336 - val_acc: 0.7812
Epoch 139/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0415 - acc: 0.9896 - val_loss: 1.0318 - val_acc: 0.7812
Epoch 140/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0418 - acc: 0.9896 - val_loss: 1.0346 - val_acc: 0.7812
Epoch 141/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0597 - acc: 0.9896 - val_loss: 1.0332 - val_acc: 0.7812
Epoch 142/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0198 - acc: 0.9896 - val_loss: 1.0301 - val_acc: 0.7812
Epoch 143/250
3/3 [==============================] - 1s 189ms/step - loss: 0.1144 - acc: 0.9688 - val_loss: 1.0357 - val_acc: 0.7812
Epoch 144/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0315 - acc: 0.9896 - val_loss: 1.0361 - val_acc: 0.7812
Epoch 145/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0241 - acc: 1.0000 - val_loss: 1.0385 - val_acc: 0.7812
Epoch 146/250
3/3 [==============================] - 1s 185ms/step - loss: 0.0324 - acc: 0.9788 - val_loss: 1.0359 - val_acc: 0.7812
Epoch 147/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0305 - acc: 0.9896 - val_loss: 1.0304 - val_acc: 0.7812
Epoch 148/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0101 - acc: 1.0000 - val_loss: 1.0299 - val_acc: 0.7812
Epoch 149/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0488 - acc: 0.9792 - val_loss: 1.0296 - val_acc: 0.7812
Epoch 150/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0354 - acc: 1.0000 - val_loss: 1.0318 - val_acc: 0.7812
Epoch 151/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0181 - acc: 1.0000 - val_loss: 1.0318 - val_acc: 0.7812
Epoch 152/250
3/3 [==============================] - 1s 191ms/step - loss: 0.0102 - acc: 1.0000 - val_loss: 1.0303 - val_acc: 0.7812
Epoch 153/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0440 - acc: 0.9896 - val_loss: 1.0318 - val_acc: 0.7812
Epoch 154/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0424 - acc: 0.9896 - val_loss: 1.0293 - val_acc: 0.7812
Epoch 155/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0296 - acc: 0.9896 - val_loss: 1.0286 - val_acc: 0.7812
Epoch 156/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0476 - acc: 0.9791 - val_loss: 1.0278 - val_acc: 0.7812
Epoch 157/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0233 - acc: 0.9896 - val_loss: 1.0270 - val_acc: 0.7812
Epoch 158/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0541 - acc: 0.9789 - val_loss: 1.0247 - val_acc: 0.7812
Epoch 159/250
3/3 [==============================] - 1s 190ms/step - loss: 0.1211 - acc: 0.9580 - val_loss: 1.0273 - val_acc: 0.7812
Epoch 160/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0497 - acc: 0.9896 - val_loss: 1.0245 - val_acc: 0.7812
Epoch 161/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0073 - acc: 1.0000 - val_loss: 1.0246 - val_acc: 0.7812
Epoch 162/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0105 - acc: 1.0000 - val_loss: 1.0245 - val_acc: 0.7812
Epoch 163/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0120 - acc: 1.0000 - val_loss: 1.0241 - val_acc: 0.7812
Epoch 164/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0378 - acc: 0.9896 - val_loss: 1.0279 - val_acc: 0.7812
Epoch 165/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0148 - acc: 0.9896 - val_loss: 1.0298 - val_acc: 0.7812
Epoch 166/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0199 - acc: 0.9896 - val_loss: 1.0293 - val_acc: 0.7812
Epoch 167/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0175 - acc: 1.0000 - val_loss: 1.0286 - val_acc: 0.7812
Epoch 168/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0145 - acc: 1.0000 - val_loss: 1.0303 - val_acc: 0.7812
Epoch 169/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0057 - acc: 1.0000 - val_loss: 1.0345 - val_acc: 0.7812
Epoch 170/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0114 - acc: 1.0000 - val_loss: 1.0320 - val_acc: 0.7812
Epoch 171/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0304 - acc: 0.9789 - val_loss: 1.0337 - val_acc: 0.7812
Epoch 172/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0086 - acc: 1.0000 - val_loss: 1.0334 - val_acc: 0.7812
Epoch 173/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0200 - acc: 0.9893 - val_loss: 1.0346 - val_acc: 0.7812
Epoch 174/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0170 - acc: 1.0000 - val_loss: 1.0336 - val_acc: 0.7812
Epoch 175/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0104 - acc: 1.0000 - val_loss: 1.0354 - val_acc: 0.7812
Epoch 176/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0072 - acc: 1.0000 - val_loss: 1.0341 - val_acc: 0.7812
Epoch 177/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0282 - acc: 0.9896 - val_loss: 1.0373 - val_acc: 0.7812
Epoch 178/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0165 - acc: 1.0000 - val_loss: 1.0382 - val_acc: 0.7812
Epoch 179/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0114 - acc: 1.0000 - val_loss: 1.0394 - val_acc: 0.7812
Epoch 180/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0194 - acc: 0.9893 - val_loss: 1.0391 - val_acc: 0.7812
Epoch 181/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0185 - acc: 1.0000 - val_loss: 1.0383 - val_acc: 0.7812
Epoch 182/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0349 - acc: 0.9896 - val_loss: 1.0413 - val_acc: 0.7812
Epoch 183/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0265 - acc: 0.9893 - val_loss: 1.0412 - val_acc: 0.7812
Epoch 184/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0132 - acc: 1.0000 - val_loss: 1.0429 - val_acc: 0.7812
Epoch 185/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0041 - acc: 1.0000 - val_loss: 1.0429 - val_acc: 0.7812
Epoch 186/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0445 - acc: 0.9789 - val_loss: 1.0443 - val_acc: 0.7812
Epoch 187/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0082 - acc: 1.0000 - val_loss: 1.0445 - val_acc: 0.7812
Epoch 188/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0178 - acc: 1.0000 - val_loss: 1.0444 - val_acc: 0.7812
Epoch 189/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0431 - acc: 0.9684 - val_loss: 1.0487 - val_acc: 0.7812
Epoch 190/250
3/3 [==============================] - 1s 191ms/step - loss: 0.0227 - acc: 1.0000 - val_loss: 1.0468 - val_acc: 0.7812
Epoch 191/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0244 - acc: 0.9896 - val_loss: 1.0499 - val_acc: 0.7812
Epoch 192/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0152 - acc: 0.9896 - val_loss: 1.0480 - val_acc: 0.7812
Epoch 193/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0080 - acc: 1.0000 - val_loss: 1.0478 - val_acc: 0.7812
Epoch 194/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0116 - acc: 1.0000 - val_loss: 1.0514 - val_acc: 0.7812
Epoch 195/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0137 - acc: 1.0000 - val_loss: 1.0517 - val_acc: 0.7812
Epoch 196/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0099 - acc: 1.0000 - val_loss: 1.0509 - val_acc: 0.7812
Epoch 197/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0415 - acc: 0.9792 - val_loss: 1.0543 - val_acc: 0.7812
Epoch 198/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0125 - acc: 1.0000 - val_loss: 1.0511 - val_acc: 0.7812
Epoch 199/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0438 - acc: 0.9789 - val_loss: 1.0552 - val_acc: 0.7812
Epoch 200/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0227 - acc: 0.9896 - val_loss: 1.0541 - val_acc: 0.7812
Epoch 201/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0427 - acc: 0.9896 - val_loss: 1.0537 - val_acc: 0.7812
Epoch 202/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0202 - acc: 0.9893 - val_loss: 1.0515 - val_acc: 0.7812
Epoch 203/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0357 - acc: 0.9896 - val_loss: 1.0505 - val_acc: 0.7812
Epoch 204/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0254 - acc: 0.9896 - val_loss: 1.0529 - val_acc: 0.7812
Epoch 205/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0245 - acc: 0.9896 - val_loss: 1.0532 - val_acc: 0.7812
Epoch 206/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0175 - acc: 1.0000 - val_loss: 1.0519 - val_acc: 0.7812
Epoch 207/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0303 - acc: 0.9896 - val_loss: 1.0564 - val_acc: 0.7812
Epoch 208/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0270 - acc: 0.9896 - val_loss: 1.0549 - val_acc: 0.7812
Epoch 209/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0311 - acc: 0.9896 - val_loss: 1.0568 - val_acc: 0.7812
Epoch 210/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0150 - acc: 0.9893 - val_loss: 1.0595 - val_acc: 0.7812
Epoch 211/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0212 - acc: 1.0000 - val_loss: 1.0550 - val_acc: 0.7812
Epoch 212/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0224 - acc: 0.9893 - val_loss: 1.0577 - val_acc: 0.7812
Epoch 213/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0275 - acc: 0.9896 - val_loss: 1.0568 - val_acc: 0.7812
Epoch 214/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0134 - acc: 1.0000 - val_loss: 1.0599 - val_acc: 0.7812
Epoch 215/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0129 - acc: 1.0000 - val_loss: 1.0607 - val_acc: 0.7812
Epoch 216/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0067 - acc: 1.0000 - val_loss: 1.0594 - val_acc: 0.7812
Epoch 217/250
3/3 [==============================] - 1s 186ms/step - loss: 0.0161 - acc: 1.0000 - val_loss: 1.0592 - val_acc: 0.7812
Epoch 218/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0117 - acc: 1.0000 - val_loss: 1.0604 - val_acc: 0.7812
Epoch 219/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0261 - acc: 0.9896 - val_loss: 1.0597 - val_acc: 0.7812
Epoch 220/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0211 - acc: 1.0000 - val_loss: 1.0579 - val_acc: 0.7812
Epoch 221/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0105 - acc: 1.0000 - val_loss: 1.0574 - val_acc: 0.7812
Epoch 222/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0146 - acc: 0.9896 - val_loss: 1.0592 - val_acc: 0.7812
Epoch 223/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0228 - acc: 0.9896 - val_loss: 1.0581 - val_acc: 0.7812
Epoch 224/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0102 - acc: 1.0000 - val_loss: 1.0597 - val_acc: 0.7812
Epoch 225/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0058 - acc: 1.0000 - val_loss: 1.0582 - val_acc: 0.7812
Epoch 226/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0139 - acc: 1.0000 - val_loss: 1.0582 - val_acc: 0.7812
Epoch 227/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0103 - acc: 1.0000 - val_loss: 1.0571 - val_acc: 0.7812
Epoch 228/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0135 - acc: 1.0000 - val_loss: 1.0549 - val_acc: 0.7812
Epoch 229/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0157 - acc: 1.0000 - val_loss: 1.0539 - val_acc: 0.7812
Epoch 230/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0333 - acc: 0.9893 - val_loss: 1.0536 - val_acc: 0.7812
Epoch 231/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0114 - acc: 1.0000 - val_loss: 1.0487 - val_acc: 0.7812
Epoch 232/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0535 - acc: 0.9789 - val_loss: 1.0537 - val_acc: 0.7812
Epoch 233/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0209 - acc: 0.9896 - val_loss: 1.0557 - val_acc: 0.7812
Epoch 234/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0132 - acc: 1.0000 - val_loss: 1.0556 - val_acc: 0.7812
Epoch 235/250
3/3 [==============================] - 1s 191ms/step - loss: 0.0243 - acc: 0.9896 - val_loss: 1.0548 - val_acc: 0.7812
Epoch 236/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0237 - acc: 0.9896 - val_loss: 1.0570 - val_acc: 0.7812
Epoch 237/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0152 - acc: 1.0000 - val_loss: 1.0589 - val_acc: 0.7812
Epoch 238/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0241 - acc: 0.9896 - val_loss: 1.0593 - val_acc: 0.7812
Epoch 239/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0034 - acc: 1.0000 - val_loss: 1.0629 - val_acc: 0.7812
Epoch 240/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0178 - acc: 1.0000 - val_loss: 1.0634 - val_acc: 0.7812
Epoch 241/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0173 - acc: 1.0000 - val_loss: 1.0617 - val_acc: 0.7812
Epoch 242/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0214 - acc: 0.9896 - val_loss: 1.0624 - val_acc: 0.7812
Epoch 243/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0192 - acc: 1.0000 - val_loss: 1.0668 - val_acc: 0.7812
Epoch 244/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0135 - acc: 1.0000 - val_loss: 1.0633 - val_acc: 0.7812
Epoch 245/250
3/3 [==============================] - 1s 189ms/step - loss: 0.0278 - acc: 0.9896 - val_loss: 1.0611 - val_acc: 0.7812
Epoch 246/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0089 - acc: 1.0000 - val_loss: 1.0657 - val_acc: 0.7812
Epoch 247/250
3/3 [==============================] - 1s 190ms/step - loss: 0.0186 - acc: 1.0000 - val_loss: 1.0674 - val_acc: 0.7812
Epoch 248/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0150 - acc: 0.9893 - val_loss: 1.0664 - val_acc: 0.7812
Epoch 249/250
3/3 [==============================] - 1s 187ms/step - loss: 0.0656 - acc: 0.9575 - val_loss: 1.0677 - val_acc: 0.7812
Epoch 250/250
3/3 [==============================] - 1s 188ms/step - loss: 0.0123 - acc: 1.0000 - val_loss: 1.0653 - val_acc: 0.7812

model.save("cam_grid_prostate_resnet50_7812.h5")

model.summary()

__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_1 (InputLayer)            (None, 224, 224, 1)  0                                            
__________________________________________________________________________________________________
conv1_pad (ZeroPadding2D)       (None, 230, 230, 1)  0           input_1[0][0]                    
__________________________________________________________________________________________________
conv1 (Conv2D)                  (None, 112, 112, 64) 3200        conv1_pad[0][0]                  
__________________________________________________________________________________________________
bn_conv1 (BatchNormalization)   (None, 112, 112, 64) 256         conv1[0][0]                      
__________________________________________________________________________________________________
activation_1 (Activation)       (None, 112, 112, 64) 0           bn_conv1[0][0]                   
__________________________________________________________________________________________________
pool1_pad (ZeroPadding2D)       (None, 114, 114, 64) 0           activation_1[0][0]               
__________________________________________________________________________________________________
max_pooling2d_1 (MaxPooling2D)  (None, 56, 56, 64)   0           pool1_pad[0][0]                  
__________________________________________________________________________________________________
res2a_branch2a (Conv2D)         (None, 56, 56, 64)   4160        max_pooling2d_1[0][0]            
__________________________________________________________________________________________________
bn2a_branch2a (BatchNormalizati (None, 56, 56, 64)   256         res2a_branch2a[0][0]             
__________________________________________________________________________________________________
activation_2 (Activation)       (None, 56, 56, 64)   0           bn2a_branch2a[0][0]              
__________________________________________________________________________________________________
res2a_branch2b (Conv2D)         (None, 56, 56, 64)   36928       activation_2[0][0]               
__________________________________________________________________________________________________
bn2a_branch2b (BatchNormalizati (None, 56, 56, 64)   256         res2a_branch2b[0][0]             
__________________________________________________________________________________________________
activation_3 (Activation)       (None, 56, 56, 64)   0           bn2a_branch2b[0][0]              
__________________________________________________________________________________________________
res2a_branch2c (Conv2D)         (None, 56, 56, 256)  16640       activation_3[0][0]               
__________________________________________________________________________________________________
res2a_branch1 (Conv2D)          (None, 56, 56, 256)  16640       max_pooling2d_1[0][0]            
__________________________________________________________________________________________________
bn2a_branch2c (BatchNormalizati (None, 56, 56, 256)  1024        res2a_branch2c[0][0]             
__________________________________________________________________________________________________
bn2a_branch1 (BatchNormalizatio (None, 56, 56, 256)  1024        res2a_branch1[0][0]              
__________________________________________________________________________________________________
add_1 (Add)                     (None, 56, 56, 256)  0           bn2a_branch2c[0][0]              
                                                                 bn2a_branch1[0][0]               
__________________________________________________________________________________________________
activation_4 (Activation)       (None, 56, 56, 256)  0           add_1[0][0]                      
__________________________________________________________________________________________________
res2b_branch2a (Conv2D)         (None, 56, 56, 64)   16448       activation_4[0][0]               
__________________________________________________________________________________________________
bn2b_branch2a (BatchNormalizati (None, 56, 56, 64)   256         res2b_branch2a[0][0]             
__________________________________________________________________________________________________
activation_5 (Activation)       (None, 56, 56, 64)   0           bn2b_branch2a[0][0]              
__________________________________________________________________________________________________
res2b_branch2b (Conv2D)         (None, 56, 56, 64)   36928       activation_5[0][0]               
__________________________________________________________________________________________________
bn2b_branch2b (BatchNormalizati (None, 56, 56, 64)   256         res2b_branch2b[0][0]             
__________________________________________________________________________________________________
activation_6 (Activation)       (None, 56, 56, 64)   0           bn2b_branch2b[0][0]              
__________________________________________________________________________________________________
res2b_branch2c (Conv2D)         (None, 56, 56, 256)  16640       activation_6[0][0]               
__________________________________________________________________________________________________
bn2b_branch2c (BatchNormalizati (None, 56, 56, 256)  1024        res2b_branch2c[0][0]             
__________________________________________________________________________________________________
add_2 (Add)                     (None, 56, 56, 256)  0           bn2b_branch2c[0][0]              
                                                                 activation_4[0][0]               
__________________________________________________________________________________________________
activation_7 (Activation)       (None, 56, 56, 256)  0           add_2[0][0]                      
__________________________________________________________________________________________________
res2c_branch2a (Conv2D)         (None, 56, 56, 64)   16448       activation_7[0][0]               
__________________________________________________________________________________________________
bn2c_branch2a (BatchNormalizati (None, 56, 56, 64)   256         res2c_branch2a[0][0]             
__________________________________________________________________________________________________
activation_8 (Activation)       (None, 56, 56, 64)   0           bn2c_branch2a[0][0]              
__________________________________________________________________________________________________
res2c_branch2b (Conv2D)         (None, 56, 56, 64)   36928       activation_8[0][0]               
__________________________________________________________________________________________________
bn2c_branch2b (BatchNormalizati (None, 56, 56, 64)   256         res2c_branch2b[0][0]             
__________________________________________________________________________________________________
activation_9 (Activation)       (None, 56, 56, 64)   0           bn2c_branch2b[0][0]              
__________________________________________________________________________________________________
res2c_branch2c (Conv2D)         (None, 56, 56, 256)  16640       activation_9[0][0]               
__________________________________________________________________________________________________
bn2c_branch2c (BatchNormalizati (None, 56, 56, 256)  1024        res2c_branch2c[0][0]             
__________________________________________________________________________________________________
add_3 (Add)                     (None, 56, 56, 256)  0           bn2c_branch2c[0][0]              
                                                                 activation_7[0][0]               
__________________________________________________________________________________________________
activation_10 (Activation)      (None, 56, 56, 256)  0           add_3[0][0]                      
__________________________________________________________________________________________________
res3a_branch2a (Conv2D)         (None, 28, 28, 128)  32896       activation_10[0][0]              
__________________________________________________________________________________________________
bn3a_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3a_branch2a[0][0]             
__________________________________________________________________________________________________
activation_11 (Activation)      (None, 28, 28, 128)  0           bn3a_branch2a[0][0]              
__________________________________________________________________________________________________
res3a_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_11[0][0]              
__________________________________________________________________________________________________
bn3a_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3a_branch2b[0][0]             
__________________________________________________________________________________________________
activation_12 (Activation)      (None, 28, 28, 128)  0           bn3a_branch2b[0][0]              
__________________________________________________________________________________________________
res3a_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_12[0][0]              
__________________________________________________________________________________________________
res3a_branch1 (Conv2D)          (None, 28, 28, 512)  131584      activation_10[0][0]              
__________________________________________________________________________________________________
bn3a_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3a_branch2c[0][0]             
__________________________________________________________________________________________________
bn3a_branch1 (BatchNormalizatio (None, 28, 28, 512)  2048        res3a_branch1[0][0]              
__________________________________________________________________________________________________
add_4 (Add)                     (None, 28, 28, 512)  0           bn3a_branch2c[0][0]              
                                                                 bn3a_branch1[0][0]               
__________________________________________________________________________________________________
activation_13 (Activation)      (None, 28, 28, 512)  0           add_4[0][0]                      
__________________________________________________________________________________________________
res3b_branch2a (Conv2D)         (None, 28, 28, 128)  65664       activation_13[0][0]              
__________________________________________________________________________________________________
bn3b_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3b_branch2a[0][0]             
__________________________________________________________________________________________________
activation_14 (Activation)      (None, 28, 28, 128)  0           bn3b_branch2a[0][0]              
__________________________________________________________________________________________________
res3b_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_14[0][0]              
__________________________________________________________________________________________________
bn3b_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3b_branch2b[0][0]             
__________________________________________________________________________________________________
activation_15 (Activation)      (None, 28, 28, 128)  0           bn3b_branch2b[0][0]              
__________________________________________________________________________________________________
res3b_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_15[0][0]              
__________________________________________________________________________________________________
bn3b_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3b_branch2c[0][0]             
__________________________________________________________________________________________________
add_5 (Add)                     (None, 28, 28, 512)  0           bn3b_branch2c[0][0]              
                                                                 activation_13[0][0]              
__________________________________________________________________________________________________
activation_16 (Activation)      (None, 28, 28, 512)  0           add_5[0][0]                      
__________________________________________________________________________________________________
res3c_branch2a (Conv2D)         (None, 28, 28, 128)  65664       activation_16[0][0]              
__________________________________________________________________________________________________
bn3c_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3c_branch2a[0][0]             
__________________________________________________________________________________________________
activation_17 (Activation)      (None, 28, 28, 128)  0           bn3c_branch2a[0][0]              
__________________________________________________________________________________________________
res3c_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_17[0][0]              
__________________________________________________________________________________________________
bn3c_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3c_branch2b[0][0]             
__________________________________________________________________________________________________
activation_18 (Activation)      (None, 28, 28, 128)  0           bn3c_branch2b[0][0]              
__________________________________________________________________________________________________
res3c_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_18[0][0]              
__________________________________________________________________________________________________
bn3c_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3c_branch2c[0][0]             
__________________________________________________________________________________________________
add_6 (Add)                     (None, 28, 28, 512)  0           bn3c_branch2c[0][0]              
                                                                 activation_16[0][0]              
__________________________________________________________________________________________________
activation_19 (Activation)      (None, 28, 28, 512)  0           add_6[0][0]                      
__________________________________________________________________________________________________
res3d_branch2a (Conv2D)         (None, 28, 28, 128)  65664       activation_19[0][0]              
__________________________________________________________________________________________________
bn3d_branch2a (BatchNormalizati (None, 28, 28, 128)  512         res3d_branch2a[0][0]             
__________________________________________________________________________________________________
activation_20 (Activation)      (None, 28, 28, 128)  0           bn3d_branch2a[0][0]              
__________________________________________________________________________________________________
res3d_branch2b (Conv2D)         (None, 28, 28, 128)  147584      activation_20[0][0]              
__________________________________________________________________________________________________
bn3d_branch2b (BatchNormalizati (None, 28, 28, 128)  512         res3d_branch2b[0][0]             
__________________________________________________________________________________________________
activation_21 (Activation)      (None, 28, 28, 128)  0           bn3d_branch2b[0][0]              
__________________________________________________________________________________________________
res3d_branch2c (Conv2D)         (None, 28, 28, 512)  66048       activation_21[0][0]              
__________________________________________________________________________________________________
bn3d_branch2c (BatchNormalizati (None, 28, 28, 512)  2048        res3d_branch2c[0][0]             
__________________________________________________________________________________________________
add_7 (Add)                     (None, 28, 28, 512)  0           bn3d_branch2c[0][0]              
                                                                 activation_19[0][0]              
__________________________________________________________________________________________________
activation_22 (Activation)      (None, 28, 28, 512)  0           add_7[0][0]                      
__________________________________________________________________________________________________
res4a_branch2a (Conv2D)         (None, 14, 14, 256)  131328      activation_22[0][0]              
__________________________________________________________________________________________________
bn4a_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4a_branch2a[0][0]             
__________________________________________________________________________________________________
activation_23 (Activation)      (None, 14, 14, 256)  0           bn4a_branch2a[0][0]              
__________________________________________________________________________________________________
res4a_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_23[0][0]              
__________________________________________________________________________________________________
bn4a_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4a_branch2b[0][0]             
__________________________________________________________________________________________________
activation_24 (Activation)      (None, 14, 14, 256)  0           bn4a_branch2b[0][0]              
__________________________________________________________________________________________________
res4a_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_24[0][0]              
__________________________________________________________________________________________________
res4a_branch1 (Conv2D)          (None, 14, 14, 1024) 525312      activation_22[0][0]              
__________________________________________________________________________________________________
bn4a_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4a_branch2c[0][0]             
__________________________________________________________________________________________________
bn4a_branch1 (BatchNormalizatio (None, 14, 14, 1024) 4096        res4a_branch1[0][0]              
__________________________________________________________________________________________________
add_8 (Add)                     (None, 14, 14, 1024) 0           bn4a_branch2c[0][0]              
                                                                 bn4a_branch1[0][0]               
__________________________________________________________________________________________________
activation_25 (Activation)      (None, 14, 14, 1024) 0           add_8[0][0]                      
__________________________________________________________________________________________________
res4b_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_25[0][0]              
__________________________________________________________________________________________________
bn4b_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4b_branch2a[0][0]             
__________________________________________________________________________________________________
activation_26 (Activation)      (None, 14, 14, 256)  0           bn4b_branch2a[0][0]              
__________________________________________________________________________________________________
res4b_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_26[0][0]              
__________________________________________________________________________________________________
bn4b_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4b_branch2b[0][0]             
__________________________________________________________________________________________________
activation_27 (Activation)      (None, 14, 14, 256)  0           bn4b_branch2b[0][0]              
__________________________________________________________________________________________________
res4b_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_27[0][0]              
__________________________________________________________________________________________________
bn4b_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4b_branch2c[0][0]             
__________________________________________________________________________________________________
add_9 (Add)                     (None, 14, 14, 1024) 0           bn4b_branch2c[0][0]              
                                                                 activation_25[0][0]              
__________________________________________________________________________________________________
activation_28 (Activation)      (None, 14, 14, 1024) 0           add_9[0][0]                      
__________________________________________________________________________________________________
res4c_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_28[0][0]              
__________________________________________________________________________________________________
bn4c_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4c_branch2a[0][0]             
__________________________________________________________________________________________________
activation_29 (Activation)      (None, 14, 14, 256)  0           bn4c_branch2a[0][0]              
__________________________________________________________________________________________________
res4c_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_29[0][0]              
__________________________________________________________________________________________________
bn4c_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4c_branch2b[0][0]             
__________________________________________________________________________________________________
activation_30 (Activation)      (None, 14, 14, 256)  0           bn4c_branch2b[0][0]              
__________________________________________________________________________________________________
res4c_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_30[0][0]              
__________________________________________________________________________________________________
bn4c_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4c_branch2c[0][0]             
__________________________________________________________________________________________________
add_10 (Add)                    (None, 14, 14, 1024) 0           bn4c_branch2c[0][0]              
                                                                 activation_28[0][0]              
__________________________________________________________________________________________________
activation_31 (Activation)      (None, 14, 14, 1024) 0           add_10[0][0]                     
__________________________________________________________________________________________________
res4d_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_31[0][0]              
__________________________________________________________________________________________________
bn4d_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4d_branch2a[0][0]             
__________________________________________________________________________________________________
activation_32 (Activation)      (None, 14, 14, 256)  0           bn4d_branch2a[0][0]              
__________________________________________________________________________________________________
res4d_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_32[0][0]              
__________________________________________________________________________________________________
bn4d_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4d_branch2b[0][0]             
__________________________________________________________________________________________________
activation_33 (Activation)      (None, 14, 14, 256)  0           bn4d_branch2b[0][0]              
__________________________________________________________________________________________________
res4d_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_33[0][0]              
__________________________________________________________________________________________________
bn4d_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4d_branch2c[0][0]             
__________________________________________________________________________________________________
add_11 (Add)                    (None, 14, 14, 1024) 0           bn4d_branch2c[0][0]              
                                                                 activation_31[0][0]              
__________________________________________________________________________________________________
activation_34 (Activation)      (None, 14, 14, 1024) 0           add_11[0][0]                     
__________________________________________________________________________________________________
res4e_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_34[0][0]              
__________________________________________________________________________________________________
bn4e_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4e_branch2a[0][0]             
__________________________________________________________________________________________________
activation_35 (Activation)      (None, 14, 14, 256)  0           bn4e_branch2a[0][0]              
__________________________________________________________________________________________________
res4e_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_35[0][0]              
__________________________________________________________________________________________________
bn4e_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4e_branch2b[0][0]             
__________________________________________________________________________________________________
activation_36 (Activation)      (None, 14, 14, 256)  0           bn4e_branch2b[0][0]              
__________________________________________________________________________________________________
res4e_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_36[0][0]              
__________________________________________________________________________________________________
bn4e_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4e_branch2c[0][0]             
__________________________________________________________________________________________________
add_12 (Add)                    (None, 14, 14, 1024) 0           bn4e_branch2c[0][0]              
                                                                 activation_34[0][0]              
__________________________________________________________________________________________________
activation_37 (Activation)      (None, 14, 14, 1024) 0           add_12[0][0]                     
__________________________________________________________________________________________________
res4f_branch2a (Conv2D)         (None, 14, 14, 256)  262400      activation_37[0][0]              
__________________________________________________________________________________________________
bn4f_branch2a (BatchNormalizati (None, 14, 14, 256)  1024        res4f_branch2a[0][0]             
__________________________________________________________________________________________________
activation_38 (Activation)      (None, 14, 14, 256)  0           bn4f_branch2a[0][0]              
__________________________________________________________________________________________________
res4f_branch2b (Conv2D)         (None, 14, 14, 256)  590080      activation_38[0][0]              
__________________________________________________________________________________________________
bn4f_branch2b (BatchNormalizati (None, 14, 14, 256)  1024        res4f_branch2b[0][0]             
__________________________________________________________________________________________________
activation_39 (Activation)      (None, 14, 14, 256)  0           bn4f_branch2b[0][0]              
__________________________________________________________________________________________________
res4f_branch2c (Conv2D)         (None, 14, 14, 1024) 263168      activation_39[0][0]              
__________________________________________________________________________________________________
bn4f_branch2c (BatchNormalizati (None, 14, 14, 1024) 4096        res4f_branch2c[0][0]             
__________________________________________________________________________________________________
add_13 (Add)                    (None, 14, 14, 1024) 0           bn4f_branch2c[0][0]              
                                                                 activation_37[0][0]              
__________________________________________________________________________________________________
activation_40 (Activation)      (None, 14, 14, 1024) 0           add_13[0][0]                     
__________________________________________________________________________________________________
res5a_branch2a (Conv2D)         (None, 7, 7, 512)    524800      activation_40[0][0]              
__________________________________________________________________________________________________
bn5a_branch2a (BatchNormalizati (None, 7, 7, 512)    2048        res5a_branch2a[0][0]             
__________________________________________________________________________________________________
activation_41 (Activation)      (None, 7, 7, 512)    0           bn5a_branch2a[0][0]              
__________________________________________________________________________________________________
res5a_branch2b (Conv2D)         (None, 7, 7, 512)    2359808     activation_41[0][0]              
__________________________________________________________________________________________________
bn5a_branch2b (BatchNormalizati (None, 7, 7, 512)    2048        res5a_branch2b[0][0]             
__________________________________________________________________________________________________
activation_42 (Activation)      (None, 7, 7, 512)    0           bn5a_branch2b[0][0]              
__________________________________________________________________________________________________
res5a_branch2c (Conv2D)         (None, 7, 7, 2048)   1050624     activation_42[0][0]              
__________________________________________________________________________________________________
res5a_branch1 (Conv2D)          (None, 7, 7, 2048)   2099200     activation_40[0][0]              
__________________________________________________________________________________________________
bn5a_branch2c (BatchNormalizati (None, 7, 7, 2048)   8192        res5a_branch2c[0][0]             
__________________________________________________________________________________________________
bn5a_branch1 (BatchNormalizatio (None, 7, 7, 2048)   8192        res5a_branch1[0][0]              
__________________________________________________________________________________________________
add_14 (Add)                    (None, 7, 7, 2048)   0           bn5a_branch2c[0][0]              
                                                                 bn5a_branch1[0][0]               
__________________________________________________________________________________________________
activation_43 (Activation)      (None, 7, 7, 2048)   0           add_14[0][0]                     
__________________________________________________________________________________________________
res5b_branch2a (Conv2D)         (None, 7, 7, 512)    1049088     activation_43[0][0]              
__________________________________________________________________________________________________
bn5b_branch2a (BatchNormalizati (None, 7, 7, 512)    2048        res5b_branch2a[0][0]             
__________________________________________________________________________________________________
activation_44 (Activation)      (None, 7, 7, 512)    0           bn5b_branch2a[0][0]              
__________________________________________________________________________________________________
res5b_branch2b (Conv2D)         (None, 7, 7, 512)    2359808     activation_44[0][0]              
__________________________________________________________________________________________________
bn5b_branch2b (BatchNormalizati (None, 7, 7, 512)    2048        res5b_branch2b[0][0]             
__________________________________________________________________________________________________
activation_45 (Activation)      (None, 7, 7, 512)    0           bn5b_branch2b[0][0]              
__________________________________________________________________________________________________
res5b_branch2c (Conv2D)         (None, 7, 7, 2048)   1050624     activation_45[0][0]              
__________________________________________________________________________________________________
bn5b_branch2c (BatchNormalizati (None, 7, 7, 2048)   8192        res5b_branch2c[0][0]             
__________________________________________________________________________________________________
add_15 (Add)                    (None, 7, 7, 2048)   0           bn5b_branch2c[0][0]              
                                                                 activation_43[0][0]              
__________________________________________________________________________________________________
activation_46 (Activation)      (None, 7, 7, 2048)   0           add_15[0][0]                     
__________________________________________________________________________________________________
res5c_branch2a (Conv2D)         (None, 7, 7, 512)    1049088     activation_46[0][0]              
__________________________________________________________________________________________________
bn5c_branch2a (BatchNormalizati (None, 7, 7, 512)    2048        res5c_branch2a[0][0]             
__________________________________________________________________________________________________
activation_47 (Activation)      (None, 7, 7, 512)    0           bn5c_branch2a[0][0]              
__________________________________________________________________________________________________
res5c_branch2b (Conv2D)         (None, 7, 7, 512)    2359808     activation_47[0][0]              
__________________________________________________________________________________________________
bn5c_branch2b (BatchNormalizati (None, 7, 7, 512)    2048        res5c_branch2b[0][0]             
__________________________________________________________________________________________________
activation_48 (Activation)      (None, 7, 7, 512)    0           bn5c_branch2b[0][0]              
__________________________________________________________________________________________________
res5c_branch2c (Conv2D)         (None, 7, 7, 2048)   1050624     activation_48[0][0]              
__________________________________________________________________________________________________
bn5c_branch2c (BatchNormalizati (None, 7, 7, 2048)   8192        res5c_branch2c[0][0]             
__________________________________________________________________________________________________
add_16 (Add)                    (None, 7, 7, 2048)   0           bn5c_branch2c[0][0]              
                                                                 activation_46[0][0]              
__________________________________________________________________________________________________
activation_49 (Activation)      (None, 7, 7, 2048)   0           add_16[0][0]                     
__________________________________________________________________________________________________
activation_50 (Activation)      (None, 7, 7, 2048)   0           activation_49[0][0]              
__________________________________________________________________________________________________
batch_normalization_1 (BatchNor (None, 7, 7, 2048)   8192        activation_50[0][0]              
__________________________________________________________________________________________________
average_pooling2d_1 (AveragePoo (None, 3, 3, 2048)   0           batch_normalization_1[0][0]      
__________________________________________________________________________________________________
flatten_1 (Flatten)             (None, 18432)        0           average_pooling2d_1[0][0]        
__________________________________________________________________________________________________
dense_1 (Dense)                 (None, 2)            36866       flatten_1[0][0]                  
==================================================================================================
Total params: 23,626,498
Trainable params: 23,569,282
Non-trainable params: 57,216
__________________________________________________________________________________________________

from vis.visualization import visualize_saliency,overlay
from vis.utils import utils
from keras import activations
from vis.visualization import visualize_cam
import matplotlib.cm as cm


# Utility to search for layer index by name. 
# Alternatively we can specify this as -1 since it corresponds to the last layer.
# layer_idx = utils.find_layer_idx(model, 0)

# Swap softmax with linear
# model.summary()



layer_idx = utils.find_layer_idx(model, 'dense_1')
model.layers[layer_idx].activation = activations.linear

model = utils.apply_modifications(model)

conv_list = np.array([2, 7, 10, 13, 14, 19, 22, 25, 29, 32, 35, 39, 42, 45, 46, 51, 54, 57, 61,
                    64, 68, 71, 74, 78, 81, 84, 85, 90, 93, 96, 100, 103, 106, 110, 113, 116,
                    120, 123, 126, 130, 133, 136, 140, 143, 146, 147, 152, 155, 158, 162, 165, 168])

 # img=cv2.imread(true_imgs[index],0)
    # img=cv2.imread('./Result/False/2.png',0)
    # img=cv2.imread('./x_pic/False/1.png',0)
img=cv2.imread('./True/CAI_RONG_JIN_100356476_slice_010_1_5.png',0)

# print(true_imgs[index])
# img=cv2.imread('./Predict_Img/3.png',0)

img=cv2.resize(img,(224,224))
print (img.shape)
img=np.reshape(img,(224,224,1))
print (img.shape)
for i in conv_list:
    print(i, model.layers[i], '\n')
    index=13

   
    for t in range(2):
# for t in range(1,30):
#     print (t)
        grads = visualize_cam(model, layer_idx,filter_indices=t, penultimate_layer_idx=i, seed_input=img, backprop_modifier='relu')
        #grads = visualize_saliency(model, layer_idx,filter_indices=t,  seed_input=img, backprop_modifier='relu')
    #     print (grads.shape)
        # Plot with 'jet' colormap to visualize as a heatmap.

    #     print (img.shape)
        print('this is layer ', i, '\n')
        plt.imshow(img[...,0],cmap=plt.cm.gray)
        plt.show()

        jet_heatmap = np.uint8(cm.jet(grads)[..., :3] * 255)
        # plt.imshow(overlay(jet_heatmap, x_val_pic[1]))

        plt.imshow(grads, cmap='jet')

        plt.show()


        from scipy.misc import imsave

        imsave('./Result/G1.jpg',grads)

    
    
# penultimate_layer = utils.find_layer_idx(model, 'conv1')
# print(penultimate_layer)

# model = utils.apply_modifications(model)

(224, 224)
(224, 224, 1)
2 <keras.layers.convolutional.Conv2D object at 0x7f85ba0b6da0> 

this is layer  2

this is layer  2

7 <keras.layers.convolutional.Conv2D object at 0x7f85ba0bb2b0> 

this is layer  7

this is layer  7

10 <keras.layers.convolutional.Conv2D object at 0x7f85ba0bb588> 

this is layer  10

this is layer  10

13 <keras.layers.convolutional.Conv2D object at 0x7f85ba0bb860> 

this is layer  13

this is layer  13

14 <keras.layers.convolutional.Conv2D object at 0x7f85ba0bb9e8> 

this is layer  14

this is layer  14